code: def kernel_pdf_invgauss_(x, sample, bw):
      """Inverse gaussian kernel density, explicit formula.
  
      Scaillet 2004
      """
      pdf = (
          1
          / np.sqrt(2 * np.pi * bw * sample**3)
          * np.exp(-1 / (2 * bw * x) * (sample / x - 2 + x / sample))
      )
      return pdf.mean(-1)
  
imports: import numpy
  from scipy import special, stats
label_desc: Use image node_id 16 for calling a global function with example usage: kernel_pdf_invgauss_(x, sample, bw) and returns: pdf